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    ESA
    2006
    Springer
    102views Algorithms» more  ESA 2006»
    Necklaces, Convolutions, and X + Y
    15 years 1 months ago
    Necklaces, Convolutions, and X + Y
    Download  compgeom.cs.uiuc.edu
    We give subquadratic algorithms that, given two necklaces each with n beads at arbitrary positions, compute the optimal rotation of the necklaces to best align the beads. Here ali...
    David Bremner, Timothy M. Chan, Erik D. Demaine, J...
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    ICCAD
    2009
    IEEE
    154views Hardware» more  ICCAD 2009»
    Pad assignment for die-stacking System-in-Package design
    14 years 7 months ago
    Pad assignment for die-stacking System-in-Package design
    Download  home.eng.iastate.edu
    Wire bonding is the most popular method to connect signals between dies in System-in-Package (SiP) design nowadays. Pad assignment, which assigns inter-die signals to die pads so ...
    Yu-Chen Lin, Wai-Kei Mak, Chris Chu, Ting-Chi Wang
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    P2P
    2008
    IEEE
    63views Communications» more  P2P 2008»
    Transaction Rate Limiters for Peer-to-Peer Systems
    15 years 4 months ago
    Transaction Rate Limiters for Peer-to-Peer Systems
    Download  research.microsoft.com
    We introduce transaction rate limiters, new mechanisms that limit (probabilistically) the maximum number of transactions a user of a peer-to-peer system can do in any given period...
    Marcos Kawazoe Aguilera, Mark Lillibridge, Xiaozho...
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    FIMI
    2004
    239views Data Mining» more  FIMI 2004»
    LCM ver. 2: Efficient Mining Algorithms for Frequent/Closed/Maximal Itemsets
    14 years 11 months ago
    LCM ver. 2: Efficient Mining Algorithms for Frequent/Closed/Maximal Itemsets
    Download  sunsite.informatik.rwth-aachen.de
    : For a transaction database, a frequent itemset is an itemset included in at least a specified number of transactions. A frequent itemset P is maximal if P is included in no other...
    Takeaki Uno, Masashi Kiyomi, Hiroki Arimura
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    IJCAI
    2003
    130views Artificial Intelligence» more  IJCAI 2003»
    Learning to Classify Texts Using Positive and Unlabeled Data
    14 years 11 months ago
    Learning to Classify Texts Using Positive and Unlabeled Data
    Download  www.cs.uic.edu
    In traditional text classification, a classifier is built using labeled training documents of every class. This paper studies a different problem. Given a set P of documents of a ...
    Xiaoli Li, Bing Liu
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